Ant Colony-Based Reinforcement Learning Algorithm for Routing in Wireless Sensor Networks
Reza GhasemAghaei, Md. Abdur Rahman, Wail Gueaieb, Abdulmotaleb El Saddik · Conference proceedings - IEEE Instrumentation/Measurement Technology Conference · 2007
The field of routing and sensor networking is an important and challenging research area of network computing today. Advancements in sensor networks enable a wide range of environmental monitoring and object tracking applications. Routing in sensor networks is a difficult problem: as the size of the network increases, routing becomes more complex. Therefore, biologically-inspired intelligent algorithms are used to tackle this problem. Ant routing has shown excellent performance for sensor networks. In this paper, we present a biologically-inspired swarm intelligence-based routing algorithm, which is suitable for sensor networks. Our proposed ant routing algorithm also meet the enhanced sensor network requirements, including energy consumption, success rate, and time delay. The paper concludes with the measurement data we have found.